29 citations · 122 across the 33 of their papers we have counts for
13 papers · 1 filter
Multi-stream Fusion for Class Incremental Learning in Pill Image Classification
Trong-Tung Nguyen, Hieu H. Pham, Phi Le Nguyen +2
Classifying pill categories from real-world images is crucial for various smart healthcare applications. Although existing approaches in image classification might achieve a good p…
Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese
Thao T. B. Nguyen, Tam M. Vo, Thang V. Nguyen +2
We propose a data collecting and annotation pipeline that extracts information from Vietnamese radiology reports to provide accurate labels for chest X-ray (CXR) images. This can b…
Enhancing Deep Learning-based 3-lead ECG Classification with Heartbeat Counting and Demographic Data Integration
Khiem H. Le, Hieu H. Pham, Thao B. T. Nguyen +2
Nowadays, an increasing number of people are being diagnosed with cardiovascular diseases (CVDs), the leading cause of death globally. The gold standard for identifying these heart…
Video-based Human Action Recognition using Deep Learning: A Review
Hieu H. Pham, Louahdi Khoudour, Alain Crouzil +2
Human action recognition is an important application domain in computer vision. Its primary aim is to accurately describe human actions and their interactions from a previously uns…
An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
Hieu H. Pham, Ha Q. Nguyen, Hieu T. Nguyen +2
Recent artificial intelligence (AI) algorithms have achieved radiologist-level performance on various medical classification tasks. However, only a few studies addressed the locali…
Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks
Thao Nguyen, Hieu H. Pham, Huy Khiem Le +3
The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, raising the need to develop novel tools to provide rapid and cost-effective screening and diag…
Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices
Dat T. Ngo, Thao T. B. Nguyen, Hieu T. Nguyen +3
The rapid development in representation learning techniques such as deep neural networks and the availability of large-scale, well-annotated medical imaging datasets have to a rapi…
LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification
Khiem H. Le, Hieu H. Pham, Thao BT. Nguyen +3
Cardiovascular diseases (CVDs) are a group of heart and blood vessel disorders that is one of the most serious dangers to human health, and the number of such patients is still gro…
Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling
Binh T. Dao, Thang V. Nguyen, Hieu H. Pham +1
A fully automated system for interpreting abdominal computed tomography (CT) scans with multiple phases of contrast enhancement requires an accurate classification of the phases. T…
Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis
Khiem H. Le, Tuan V. Tran, Hieu H. Pham +3
Building an accurate computer-aided diagnosis system based on data-driven approaches requires a large amount of high-quality labeled data. In medical imaging analysis, multiple exp…
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography
Hieu T. Nguyen, Ha Q. Nguyen, Hieu H. Pham +4
Mammography, or breast X-ray, is the most widely used imaging modality to detect cancer and other breast diseases. Recent studies have shown that deep learning-based computer-assis…
PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children
Hieu H. Pham, Ngoc H. Nguyen, Thanh T. Tran +2
The development of diagnostic models for detecting and diagnosing pediatric diseases in CXR scans is undertaken due to the lack of high-quality physician-annotated datasets. To ove…
A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms
Sam B. Tran, Huyen T. X. Nguyen, Chi Phan +2
Image augmentation techniques have been widely investigated to improve the performance of deep learning (DL) algorithms on mammography classification tasks. Recent methods have pro…